Due to the inefficiency, high labor intensity, poor sealing quality, and challenges in controlling the amount of glue applied of traditional manual gluing methods, this study proposes a solution of the automatic gluing process using multi-parameter coupling based on colloid morphology to enhance the stable control of glue amount and colloid morphology of automated gluing processes. First, an orthogonal experimental design is conducted to analyze the impact of multiple parameters on the automated gluing process, with Pearson correlation coefficient analysis used to identify the key influencing parameters. Next, gluing experiments are performed on three different gluing objects to explore the optimal gluing parameters. Ultimately, the three-dimensional detection technology is employed to acquire the point cloud data of the colloid. By utilizing point cloud data processing algorithms, more accurate positional information is obtained. The crosssectional area of the colloid is calculated using the trapezoidal numerical integration method to determine the colloid’s morphological type. Through comprehensive analysis of the multi-parameter coupled automated gluing experiments, the optimal gluing parameters are identified: a speed of 5 mm/s, a pressure of 103 kPa, a distance of 3 mm, and an angle of 90°, the glue morphology is optimal, effectively preventing problems such as glue leakage, breaks, and excessively narrow or wide glue bodies. This approach improves the efficiency and precision of the gluing process.